Investigating the factors affecting the export, efficiency, and export capacity of Iranian Dates

Authors
1 Assistant Professor, Department of Agricultural Economics, university of Tehran
2 Associate Professor, Department of Agricultural Economics, university of Tehran
3 Professor, Department of Agricultural Economics, university of Tehran
4 4. Professor, Department of Agricultural Economics, university of Tehran
Abstract
This study analyzes the current state of international trade, focusing on trade relations between Iran and other nations, as well as existing and potential capacities for future trade. It also aims to evaluate the impact of key factors on Date exports and their effects. To achieve this, the research investigates the factors influencing Iranian date exports by utilizing panel data and employing a fixed effects model from 2001 to 2023. The findings indicate that several factors positively influence Date exports. These include trade advantages, the logarithm of the exchange rate, the disparity between Iran's GDP and that of its trading partners, the logarithm of the ratio of export prices to domestic prices, and trade agreements with target countries. Conversely, the logarithm of the cost of exporting agricultural products to the target country and the impact of sanctions negatively affect Iranian date exports. During the study period, the structure of Iran's Date export market has varied between a tight and loose oligopoly. The analysis of advantage indicators shows that there is an export advantage for Dates. It is crucial to prioritize the enhancement and development of supply chains for Iran's main export products. The main challenges in the supply chain for these products involve acquiring production inputs, as well as the processes of packaging, sorting, processing, and transportation.

Keywords

Subjects


1. Abdullahi NM, Zhang Q, Shahriar S, Irshad MS, Ado AB, et al. (2022) Examining the determinants and efficiency of China’s agricultural exports using a stochastic frontier gravity model. PLOS ONE 17(9): e0274187. https://doi.org/10.1371/journal.pone.0274187.
2. Abdullahi, N. M., Huo, X., Zhang, Q., & Bolanle Azeez, A. (2021). Determinants and Potential of Agri-Food Trade Using the Stochastic Frontier Gravity Model: Empirical Evidence From Nigeria. SAGE Open, 11(4). https://doi.org/10.1177/21582440211065770 (Original work published 2021).
3. Aigner, D., Knox Lovell, C. A. and Schmidt, P. 1977. Formulation and Estimation of Stochastic Frontier Production Function Models. Journal of Econometrics, 6, 1, 21–37. doi.org/10.1016/0304-4076(77)90052-5
4. Aminizadeh, M., Mohammadi, H., Karbasi, A. and Rafiee, H., 2025. Application of Stochastic Frontier Gravity Model for Determining Seafood Export. Journal of Agricultural Science and Technology, pp.1-15.
5. Atif, R.M., Mahmood, H., Haiyun, L., Mao, H. 2019. Determinants and efficiency of Pakistan's chemical products' exports: An application of stochastic frontier gravity model. PLoS One. 14(5):e0217210. https://doi.org/10.1371/journal.pone.0217210.
6. Colloca, P., Roccato, M. and Russo S. 2024. Rally ‘round the flag effects are not for all: Trajectories of institutional trust among populist and non-populist voters. Social Science Research, Volume 119, 102986, ISSN 0049-089X, https://doi.org/10.1016/j.ssresearch.2024.102986.
7. Darko, R. O., Liu, J., Yuan, S., Sam-Amoah, L. K., and Yan, H. 2020. Irrigated agriculture for food self-sufficiency in the sub-Saharan African region. International Journal of Agricultural and Biological Engineering, 13(3), 1-12. DOI: 10.25165/j.ijabe.20201303.4397
8. De Wit, H., and Altbach, P. G. 2021. Internationalization in higher education: Global trends and recommendations for its future. Policy Reviews in Higher Education, 5(1), 28-46. https://doi.org/10.1080/23322969.2020.1820898
9. Gyamfi, B. A., Divine, Q. A., Musah, M., Taiwo, O. S. and Prusty, S. 2023. The synergistic roles of green openness and economic complexity in environmental sustainability of Europe's largest economy: Implications for technology-intensive and environmentally friendly products. Environmental Impact Assessment Review, Volume 102, 107220, ISSN 0195-9255, https://doi.org/10.1016/j.eiar.2023.107220.
10. Irfan M., Madurai E. R., Ahmad M., Mohsin M., Dagar V. and Hao Y. 2022. Prioritizing and overcoming biomass energy barriers: Application of AHP and G-TOPSIS approaches, Technological Forecasting and Social Change, Volume 177, 121524, ISSN 0040-1625, https://doi.org/10.1016/j.techfore.2022.121524.
11. Jia, Z., Wang, Y., Chen, Y., Chen, Y. 2022. The role of trade liberalization in promoting regional integration and sustainability: The case of regional comprehensive economic partnership. PLoS ONE. 17(11): e0277977. https://doi.org/ 10.1371/journal.pone.0277977
12. Kazem Pour, A. , Rafiee, H. , Noroozi, H. , Zarer, S. , Yousefzadeh, L. and Kaboudtabar, M. (2022). Prioritization of Iranian Tomato Target Markets Based on Market Competition Indicators. Journal of Agricultural Economics & Development, 36(1), 49-65. https://doi.org/10.22067/jead.2022.72231.1075
13. Kazempour Kahriz, A. , Rafiee, H. , ghaem maghami, S. T. , noroozi, H. and Ghasemi, A. 2023. Analysis of Iran's Natural Honey Export Market Structure and Prioritization of Target Countries Based on Market Attractiveness Indicators. Agricultural Economics and Development, 31(1), 49-72. 10.30490/aead.2023.355644.1372.
14. Kölling, A. 2020. Long‐run Asymmetries in Labor Demand: Estimating Wage Elasticities of Labor Demand Using a Fractional Panel Probit Model. Labour, 34(1), 26-47. https://doi.org/10.1111/labr.12163
15. Kunroo, M.H., Ahmad, I. 2023. Heckscher-Ohlin Theory or the Modern Trade Theory: How the Overall Trade Characterizes at the Global Level?. J. Quant. Econ. 21, 151–174. https://doi.org/10.1007/s40953-022-00330-x
16. Lahtinen, V., Dietrich, T. and Rundle-Thiele, S. (2020), "Long live the marketing mix. Testing the effectiveness of the commercial marketing mix in a social marketing context". Journal of Social Marketing, Vol. 10 No. 3, pp. 357-375. https://doi.org/10.1108/JSOCM-10-2018-0122
17. Mhlanga, D. (2023). Artificial Intelligence and Machine Learning for Energy Consumption and Production in Emerging Markets: A Review. Energies, 16(2), 745. https://doi.org/10.3390/en16020745
18. Nguyen, D.D. (2022), "Determinants of Vietnam's rice and coffee exports: using stochastic frontier gravity model", Journal of Asian Business and Economic Studies, Vol. 29 No. 1, pp. 19-34. https://doi.org/10.1108/JABES-05-2020-0054.
19. Noroozi, H., Rafiei, H., Yazdani, S., Hosseini, S. p. and Chizari, Amirhossein. 2022. Investigating and determining the export priorities of Iran's tomato paste product and the factors affecting it. Agricultural Economics. 16 (3), 107-143. https://doi.org/10.22034/iaes.2022.560674.1940 (in Persian with English Abstract)
20. Noroozi, H. , Rafiee, H. , Hosseini, S. , Yazdani, S. and Chizari, A. 2021. Analysis of factors affecting sugar import with emphasis on the role of research and development budgets. Journal of Sugar Beet, 37(2), 247-262. doi: 10.22092/jsb.2022.355444.1283. (in Persian with English Abstract)
21. Papke, L.E. , Wooldridge, J.M. 2008. Panel data methods for fractional response variables with an application to test pass rates, Journal of Econometrics,Volume 145, Issues 1–2,Pages 121-133,ISSN 0304-4076, https://doi.org/10.1016/j.jeconom.2008.05.009
22. Rehman, A., Ma, H., Ahmad, M., Ozturk, I. and and Işık, C. (2021). Estimating the connection of information technology, foreign direct investment, trade, renewable energy and economic progress in Pakistan: evidence from ARDL approach and cointegrating regression analysis. Environmental Science and Pollution Research, 28(36), 50623-50635. https://doi.org/10.1007/s11356-021-14303-9
23. Rehman, F.U. and Noman, A.A. (2022), "China's outward foreign direct investment and bilateral export sophistication: a cross countries panel data analysis", China Finance Review International, Vol. 12 No. 1, pp. 180-197. https://doi.org/10.1108/CFRI-04-2020-0040
24. Shibata S, Fukumoto D, Suzuki T, Ozaki K. 2020. A Comparative Study of the Market Configuration of the Japanese Pharmaceutical Market Using the Gini Coefficient and Herfindahl-Hirschman Index. Ther Innov Regul Sci., 54(5):1047-1055. doi: 10.1007/s43441-020-00122-6
25. Sun J, Luo Y., Zhou Y., 2022. The impact of regional trade agreements on the quality of export products in China’s manufacturing industry, Journal of Asian Economics, Volume 80, 101456, ISSN 1049-0078, https://doi.org/10.1016/j.asieco.2022.101456.
26. Yusuf N. and Nasrulddin V., 2024. "Significance of International Trade and National GDP as Two Integral Components of Sustainable Economic Development in Saudi Arabia," Journal of the Knowledge Economy, Springer; Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 2298-2317. DOI: 10.1007/s13132-023-01245-5
27. Zhang, C., Waris, U., Qian, L., Irfan, M., and Abdur Rehman., M. 2024. "Unleashing the dynamic linkages among natural resources, economic complexity, and sustainable economic growth: Evidence from G‐20 countries". Sustainable Development, John Wiley and Sons, Ltd., vol. 32(4), pages 3736-3752. DOI: 10.1002/sd.2845.

Articles in Press, Accepted Manuscript
Available Online from 16 September 2025